In online marketing, a landing page, sometimes known as a "lead capture page" or a "lander", or a "destination page", is a single web page that appears in response to clicking on a search engine optimized search result or an online advertisement. The landing page will usually display directed sales copy that is a logical extension of the advertisement, search result or link. Landing pages are used for lead generation. The actions that a visitor takes on a landing page is what determines an advertiser's conversion rate.
Landing pages are often linked to social media, e-mail campaigns or search engine marketing campaigns in order to enhance the effectiveness of the advertisements. The general goal of a landing page is to convert site visitors into sales or leads. If the goal is to obtain a lead, the landing page will include some method for the visitor to get into contact with the company, usually a phone number, or an inquiry form. If a sale is required, the landing page will usually have a link for the visitor to click, which will then send them to a shopping cart or a checkout area. By analyzing activity generated by the linked URL, marketers can use click-through rates and conversion rate to determine the success of an advertisement.
Maps, Directions, and Place Reviews
Types
There are two types of landing pages: reference and transactional.
References
A reference landing page presents information that is relevant to the visitor. These can display text, images, dynamic compilations of relevant links, or other elements.
Transactional
The purpose of the transactional landing page is to persuade a visitor to take action by completing a transaction. This is accomplished by providing a form that needs to be filled out. The visitor information is obtained in order to add the visitor's email address to a mailing list as a prospect. An email campaign can then be developed based on responses to transactional landing pages. The goal is to capture as much information about the visitor as possible. The ultimate goal is to convert the visitor into a customer.
Origin
Landing pages originated with the IT departments of Microsoft in late 2003 in response to poor online sales of Office. The process was tedious and time-consuming. As a result, in 2009, several startups, including Unbounce, were formed to simplify and streamline the process. The rise of cloud computing and e-commerce around 2009 provided ideal conditions for these startups to flourish. Since then the customer requirements changed, requesting integrations with other solutions such as email marketing, lead nurturing and customer relationship management systems.
Typical format
Landing pages often contain clear, concise action-oriented headlines. A good landing page explains the product offer in a clear manner and places visual emphasis on the value of the product or service presented.
Marketing experts recommend websites remove the navigation menu and limit internal and external links on the page. The form length mirrors the value of the offer. They may also include a relevant image, animation or short video. These pages also tend to contain small icons (i.e. of Facebook, or Twitter) to facilitate social media sharing.
Landing Page Background Video
Landing page optimization
Land page optimization (LPO) is one part of a broader Internet marketing process called conversion optimization, or conversion rate optimization (CRO), with the goal of improving the percentage of visitors to the website that become sales leads and customers. A landing page is a webpage that is displayed when a potential customer clicks an advertisement or a search engine result link. This webpage typically displays content that is a relevant extension of the advertisement or link. LPO aims to provide page content and appearance that makes the webpage more appealing to target audiences.
There are three major types of LPO based on targeting:
- Associative content targeting (also called rule-based optimization or passive targeting). The page content is modified based on information obtained about the visitor's search criteria, geographic information of source traffic, or other known generic parameters that can be used for explicit non-research-based consumer segmentation.
- Predictive content targeting (also called active targeting). The page content is adjusted by correlating any known information about the visitor (e.g., prior purchase behavior, personal demographic information, browsing patterns, etc.) to anticipate (desired) future actions based on predictive analytics.
- Consumer directed targeting (also called social targeting). The page content is created using the relevance of publicly available information through a mechanism based on reviews, ratings, tagging, referrals, etc.
There are two major types of LPO based on experimentation:
- Closed-ended experimentation. Consumers are exposed to several variations of landing pages, altering elements like headlines, formatting and layout while their behavior is observed in an attempt to remove distractions that will take the lead away from the page, including the primary navigation. At the conclusion of the experiment, an optimal page is selected based on the outcome of the experiment.
- Open-ended experimentation. This approach is similar to closed-ended experimentation except that more variations will be added for testing and experimentation will not stop when a winner is found. This method is used by large corporation to dynamically improve their conversion rates and improve user experience. Landing page can also be adjusted dynamically as the experiment results change to further enhance user experience.
Experimentation-based
Experimentation-based LPO can be achieved using A/B testing, multivariate LPO, and total-experience testing. These methodologies are applicable to both closed- and open-ended experimentation.
A/B testing
A/B testing, or A/B split testing, is a method for testing two versions of a webpage: version "A" and version "B". The goal is to test multiple versions of webpages (e.g., home page vs. product page) or one specific element that changes between variation A and variation B (such as having a lead form on the left hand side or having it placed on the right hand side), FAQ to determine which version is most appealing/effective. This testing method may also be known as A/B/n split testing; the n denoting more than 2 tests being measured and compared. The data for A/B testing is usually measured via click-through rate or an alternative conversion tracking method.
Testing can be conducted sequentially or in parallel. In sequential testing, often the easiest to implement, the various versions of the webpages are made available online for a specified time period. In parallel (split) testing, both versions are made available, and the traffic is divided between the two. The results of sequential split testing can be skewed by differing time periods and traffic patterns in which the different tests are run.
A/B testing has the following advantages:
- Inexpensive because existing resources and tools are used.
- Simple because no complex statistical analysis is required.
A/B testing has the following disadvantages:
- Difficult to control all external factors (e.g., campaigns, search traffic, press releases, seasonality) when using sequential testing.
- Very limited in that reliable conclusions cannot be drawn for pages that contain multiple elements that vary in each version.
Multivariate testing
Multivariate landing page optimization (MVLPO) accounts for multiple variations of visual elements (e.g., graphics, text) on a page. For example, a given page may have k choices for the title, m choices for the featured image or graphic, and n choices for the company logo. This example yields k×m×n landing page configurations.
Significant improvements can be seen through testing different copy text, form layouts, landing page images and background colours. However, not all elements produce the same improvements in conversions, and by looking at the results from different tests, it is possible to identify the elements that consistently tend to produce the greatest increase in conversions.
The first application of an experimental design for MVLPO was performed by Moskowitz Jacobs Inc. in 1998 as a simulation/demonstration project for Lego. MVLPO did not become a mainstream approach until 2003 or 2004.
MVLPO has the following advantages:
- Provides a reliable, scientifically based approach for understanding customers' preferences and optimizing their experience.
- Has evolved to be an easy-to-use approach in which not much IT involvement is required. In many cases, a few lines of JavaScript allow remote vendor servers to control changes, collect data, and analyze the results.
- Provides a foundation for open-ended experimentation.
MVLPO has the following disadvantages:
- As with any quantitative consumer research, there is a danger of GIGO (garbage in, garbage out). Ideas that are sourced from known customer touchpoints or strategic business objectives are needed to obtain optimal results.
- Focuses on optimizing one page at a time. Website experiences for most sites involve multiple pages, which are typically complex. For an e-commerce website, it is typical for a successful purchase to involve between twelve and eighteen pages; for a support site, even more pages are often required.
Total-experience testing
Total-experience testing, or experience testing, is a type of experiment-based testing in which the entire website experience of the visitor is examined using technical capabilities of the website platform (e.g., ATG, Blue Martini Software, etc.). Rather than creating multiple websites, total-experience testing uses the website platform to create several persistent experiences, and monitors which one is preferred by the customers.
An advantage of total-experience testing is that it reflects the customer's total website experience, not just the experience with a single page. Two disadvantages are that total-experience testing requires a website platform that supports experience testing, and it takes longer to obtain results than A/B testing and MVLPO.
Message matching
Message Matching is the idea of matching the pre-click message to the post-click message on the landing page. The goal of message matching is to create a landing page that directs individuals to a page on a product or subject they are expecting.
This could be done by displaying a statement to the visitors utilizing the same keywords and the right images on the landing page that was found in the advertisement they clicked on.
The messaging on the page reinforces the reason for their click, reducing or removing confusion and therefore increasing conversion rates. This improves overall user experience and reduces the bounce rate (individuals leaving the site without converting or navigating to another portion of the site) for the page. Good message matching can increase conversion by up to 50% in many cases.
Design matching
Design Matching takes the design on the display ad and repeats it on the landing page. Ensuring the look, feel and sentiment is the same in order to smooth the transition between clicking the ad and completing a conversion.
Source of the article : Wikipedia
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